Cast Operator (#5149)
* Cast Operator Cast input variable to other data type * Fix compile error * Add cast op * Follow commentsfix-typo
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#include "paddle/operators/cast_op.h"
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#include "paddle/framework/op_registry.h"
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namespace paddle {
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namespace operators {
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class CastOpProtoMaker : public framework::OpProtoAndCheckerMaker {
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public:
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CastOpProtoMaker(framework::OpProto *proto,
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framework::OpAttrChecker *op_checker)
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: OpProtoAndCheckerMaker(proto, op_checker) {
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AddInput("X", "the input tensor of cast op");
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AddOutput("Out", "the output tensor of cast op");
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AddComment(R"DOC(Cast operator.
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cast the input tensor to other data type.
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)DOC");
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AddAttr<int>("out_data_type", "output data type");
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AddAttr<int>("in_data_type", "input data type");
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}
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};
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class CastOpInferShape : public framework::InferShapeBase {
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public:
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void operator()(framework::InferShapeContext *context) const override {
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PADDLE_ENFORCE(context->HasInput("X"), "The input of cast op must be set");
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PADDLE_ENFORCE(context->HasOutput("Out"),
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"The output of cast op must be set");
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context->SetOutputDim("Out", context->GetInputDim("X"));
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context->ShareLoD("X", "Out");
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}
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};
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class CastOpGradMaker : public framework::SingleGradOpDescMaker {
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public:
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using framework::SingleGradOpDescMaker::SingleGradOpDescMaker;
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protected:
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std::unique_ptr<framework::OpDescBind> Apply() const override {
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auto grad = new framework::OpDescBind();
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grad->SetType("cast");
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grad->SetInput("X", OutputGrad("Out"));
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grad->SetOutput("Out", InputGrad("X"));
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grad->SetAttr("out_data_type", GetAttr("in_data_type"));
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grad->SetAttr("in_data_type", GetAttr("out_data_type"));
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return std::unique_ptr<framework::OpDescBind>(grad);
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}
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};
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} // namespace operators
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} // namespace paddle
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namespace ops = paddle::operators;
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using CPU = paddle::platform::CPUPlace;
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REGISTER_OP_WITH_KERNEL(cast, ops::CastOpGradMaker, ops::CastOpInferShape,
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ops::CastOpProtoMaker);
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REGISTER_OP_CPU_KERNEL(cast, ops::CastOpKernel<CPU, float>,
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ops::CastOpKernel<CPU, double>,
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ops::CastOpKernel<CPU, int>,
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ops::CastOpKernel<CPU, int64_t>);
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@ -0,0 +1,22 @@
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#include "paddle/operators/cast_op.h"
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template <typename T>
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using CastOpKernel =
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paddle::operators::CastOpKernel<paddle::platform::GPUPlace, T>;
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REGISTER_OP_GPU_KERNEL(cast, CastOpKernel<float>, CastOpKernel<double>,
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CastOpKernel<int>, CastOpKernel<int64_t>);
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#pragma once
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#include "paddle/framework/data_type.h"
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#include "paddle/framework/framework.pb.h"
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#include "paddle/framework/op_registry.h"
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#include "paddle/platform/transform.h"
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namespace paddle {
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namespace operators {
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template <typename InT, typename OutT>
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struct CastOpTransformFunctor {
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HOSTDEVICE OutT operator()(InT in) const { return static_cast<OutT>(in); }
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};
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template <typename Place, typename InT>
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struct CastOpFunctor {
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const framework::Tensor* in_;
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framework::Tensor* out_;
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const platform::DeviceContext& ctx_;
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CastOpFunctor(const framework::Tensor* in, framework::Tensor* out,
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const platform::DeviceContext& ctx)
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: in_(in), out_(out), ctx_(ctx) {}
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template <typename OutT>
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void operator()() const {
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auto* in_begin = in_->data<InT>();
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auto numel = in_->numel();
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auto* in_end = in_begin + numel;
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auto* out_begin = out_->mutable_data<OutT>(ctx_.GetPlace());
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platform::Transform<Place> trans;
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trans(ctx_, in_begin, in_end, out_begin,
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CastOpTransformFunctor<InT, OutT>());
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}
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};
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template <typename Place, typename InT>
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class CastOpKernel : public framework::OpKernel<InT> {
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public:
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void Compute(const framework::ExecutionContext& context) const override {
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auto* in = context.Input<framework::Tensor>("X");
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auto* out = context.Output<framework::Tensor>("Out");
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framework::VisitDataType(
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static_cast<framework::DataType>(context.Attr<int>("out_data_type")),
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CastOpFunctor<Place, InT>(in, out, context.device_context()));
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}
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};
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} // namespace operators
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} // namespace paddle
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@ -0,0 +1,26 @@
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import op_test
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import unittest
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import numpy as np
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import paddle.v2.framework.core as core
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class TestCastOp(op_test.OpTest):
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def setUp(self):
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ipt = np.random.random(size=[10, 10])
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self.inputs = {'X': ipt.astype('float32')}
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self.outputs = {'Out': ipt.astype('float64')}
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self.attrs = {
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'in_data_type': int(core.DataType.FP32),
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'out_data_type': int(core.DataType.FP64)
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}
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self.op_type = 'cast'
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def test_check_output(self):
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self.check_output()
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def test_grad(self):
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self.check_grad(['X'], ['Out'])
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if __name__ == '__main__':
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unittest.main()
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